Closed loop feedback in MIMO systems

ABSTRACT

Feedback bandwidth may be reduced in a closed loop MIMO system by factoring non essential information out of a beamforming matrix.

FIELD

The present invention relates generally to wireless networks, and more specifically to wireless networks that utilize multiple spatial channels.

BACKGROUND

Closed loop multiple-input-multiple-output (MIMO) systems typically transmit channel state information from a receiver to a transmitter. The transmitter may then utilize the information to do beam forming. Transmitting the channel state information consumes bandwidth that might otherwise be available for data traffic.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows a diagram of two wireless stations;

FIGS. 2, 3, 5, and 6 show flowcharts in accordance with various embodiments of the present invention; and

FIG. 4 shows an electronic system in accordance with various embodiments of the present invention.

DESCRIPTION OF EMBODIMENTS

In the following detailed description, reference is made to the accompanying drawings that show, by way of illustration, specific embodiments in which the invention may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the invention. It is to be understood that the various embodiments of the invention, although different, are not necessarily mutually exclusive. For example, a particular feature, structure, or characteristic described herein in connection with one embodiment may be implemented within other embodiments without departing from the spirit and scope of the invention. In addition, it is to be understood that the location or arrangement of individual elements within each disclosed embodiment may be modified without departing from the spirit and scope of the invention. The following detailed description is, therefore, not to be taken in a limiting sense, and the scope of the present invention is defined only by the appended claims, appropriately interpreted, along with the full range of equivalents to which the claims are entitled. In the drawings, like numerals refer to the same or similar functionality throughout the several views.

FIG. 1 shows a diagram of two wireless stations: station: 102, and station 104. In some embodiments, stations 102 and 104 are part of a wireless local area network (WLAN). For example, one or more of stations 102 and 104 may be an access point in a WLAN. Also for example, one or more of stations 102 and 104 may be a mobile station such as a laptop computer, personal digital assistant (PDA), or the like. Further, in some embodiments, stations 102 and 104 are part of a wireless wide area network (WWAN).

In some embodiments, stations 102 and 104 may operate partially in compliance with, or completely in compliance with, a wireless network standard. For example, stations 102 and 104 may operate partially in compliance with a standard such as ANSI/IEEE Std. 802.11, 1999 Edition, although this is not a limitation of the present invention. As used herein, the term “802.11” refers to any past, present, or future IEEE 802.11 standard, including, but not limited to, the 1999 edition. Also for example, stations 102 and 104 may operate partially in compliance with any other standard, such as any future IEEE personal area network standard or wide area network standard.

Stations 102 and 104 each include multiple antennas. Each of stations 102 and 104 includes “N” antennas, where N may be any number. In some embodiments, stations 102 and 104 have an unequal number of antennas. The remainder of this description discusses the case where stations 102 and 104 have an equal number of antennas, but the various embodiments of the invention are not so limited. The “channel” through which stations 102 and 104 communicate may include many possible signal paths. For example, when stations 102 and 104 are in an environment with many “reflectors” (e.g. walls, doors, or other obstructions), many signals may arrive from different paths. This condition is known as “multipath.” In some embodiments, stations 102 and 104 utilize multiple antennas to take advantage of the multipath and to increase the communications bandwidth. For example, in some embodiments, stations 102 and 104 may communicate using Multiple-Input-Multiple-Output (MIMO) techniques. In general, MIMO systems offer higher capacities by utilizing multiple spatial channels made possible by multipath.

In some embodiments, stations 102 and 104 may communicate using orthogonal frequency division multiplexing (OFDM) in each spatial channel. Multipath may introduce frequency selective fading which may cause impairments like inter-symbol interference (ISI). OFDM is effective at combating frequency selective fading in part because OFDM breaks each spatial channel into small subchannels such that each subchannel exhibits a more flat channel characteristic. Scaling appropriate for each subchannel may be implemented to correct any attenuation caused by the subchannel. Further, the data carrying capacity of each subchannel may be controlled dynamically depending on the fading characteristics of the subchannel.

MIMO systems may operate either “open loop” or “closed loop.” In open loop MIMO systems, a station estimates the state of the channel without receiving channel state information directly from another station. In general, open loop systems employ exponential decoding complexity to estimate the channel. In closed loop systems, communications bandwidth is utilized to transmit current channel state information between stations, thereby reducing the necessary decoding complexity, and also reducing overall throughput. The communications bandwidth used for this purpose is referred to herein as “feedback bandwidth.” When feedback bandwidth is reduced in closed loop MIMO systems, more bandwidth is available for data communications.

The current channel state information may be represented by an N×N unitary beamforming matrix V determined using a singular value decomposition (SVD) algorithm, and the transmitter may process an outgoing signal using the beamforming matrix V to transmit into multiple spatial channels. In a straightforward implementation, the receiver sends each element of the unitary matrix V back to transmitter. This scheme involves sending information related to the 2N² real numbers for any N×N complex unitary matrix, where N is the number of spatial channels in MIMO system.

In some embodiments of the present invention, the beamforming matrix V is represented by N²−N real numbers instead of 2N² real numbers. By sending N²−N real numbers instead of 2N² real numbers to represent the beamforming matrix, the feedback bandwidth may be reduced. Non-essential information may be factored out of the beamforming matrix and discarded prior to quantizing parameters that are used to represent the beamforming matrix. For example, non-essential phase information may be factored from each column in the beamforming matrix, and then N²−N parameters may be utilized to represent the matrix without the non-essential phase information.

A mathematical background of the SVD operation is provided below, and then examples are provided for 2×2 and 3×3 MIMO systems. In the 2×2 closed loop MIMO example, two angles in [0, π/2] and (π, −π] are used as feedback parameters. Compared to the straightforward example above, the various embodiments of the present invention represented by the 2×2 example below reduce the amount of feedback from eight real numbers to two real numbers per subcarrier. In the 3×3 closed loop MIMO example, one sign bit plus four angles between [0, π/2] and two angles between [−π, π] are used as feedback parameters. Compared to the straightforward example above, the various embodiments of the present invention represented by the 3×3 example below reduce the amount of feedback from 18 real numbers to six real numbers per subcarrier.

A transmit beamforming matrix may be found using SVD as follows: H=UDV′  (1) x=Vd  (2) where d is the N-vector of code bits for N data streams; x is the transmitted signal vector on the antennas; H is the channel matrix; H's singular value decomposition is H=UDV′; U and V are unitary; D is a diagonal matrix with H's eigenvalues; V is N×N, and N is the number of spatial channels. To obtain V at the transmitter, the transmitter may send training symbols to the receiver; the receiver may compute the matrix V′; and the receiver may feedback parameters representing V to the transmitter. As described more fully below, the number of feedback parameters used to represent V may be reduced by factoring non-essential phase information from V′ and discarding it prior to quantizing the parameters. 2×2 Beamforming Matrices

Any complex 2×2 matrix may be written as

$\begin{matrix} {V = {\begin{pmatrix} {b_{11}e^{{\mathbb{i}}\;\phi_{11}}} & {b_{12}{\mathbb{e}}^{{\mathbb{i}}\;\phi_{12}}} \\ {b_{21}{\mathbb{e}}^{{\mathbb{i}}\;\phi_{21}}} & {b_{22}{\mathbb{e}}^{{\mathbb{i}}\;\phi_{22}}} \end{pmatrix}.}} & (3) \end{matrix}$

If V is unitary i.e., VV′=I, then

$\begin{matrix} {V = \begin{pmatrix} {b_{11}{\mathbb{e}}^{{\mathbb{i}}\;\phi_{11}}} & {b_{12}{\mathbb{e}}^{{\mathbb{i}}\;\phi_{12}}} \\ {{- b_{12}}{\mathbb{e}}^{{\mathbb{i}}\;\phi_{21}}} & {b_{11}{\mathbb{e}}^{{\mathbb{i}}{({\phi_{12} + \phi_{21} - \phi_{11}})}}} \end{pmatrix}} & (4) \end{matrix}$

where b₁₁ ²+b₁₂ ²=1. We can further limit b₁₁ ε[0,1], b₁₂ ε[0,1], φ_(ij) ε[−π,π) without loss of generality. There are 4 degrees of freedom in V. After factoring the common phases for each row and column, the unitary matrix V can be written as

$\begin{matrix} {V = {{\begin{pmatrix} 1 & 0 \\ 0 & {\mathbb{e}}^{{\mathbb{i}}{({\phi_{21} - \phi_{11}})}} \end{pmatrix}\begin{pmatrix} b_{11} & b_{12} \\ {- b_{12}} & b_{11} \end{pmatrix}\begin{pmatrix} e^{{\mathbb{i}}\;\phi_{11}} & 0 \\ 0 & {\mathbb{e}}^{{\mathbb{i}}\;\phi_{12}} \end{pmatrix}} = {P_{L}\overset{\sim}{V}P_{R}}}} & (5) \end{matrix}$

where P_(L) and P_(R) are pure phase matrices and diagonal. (510, FIG. 5) P_(R) is generated by factoring phase values from each column of V, and P_(L) is found by factoring phase values from each row of V. {tilde over (V)} is a magnitude matrix that has entries consisting of scalar quantities that represent the magnitudes of the entries of V. Since b₁₁ ²+b₁₂ ²=1, {tilde over (V)} can be written as

$\begin{matrix} {{\overset{\sim}{V} = \begin{pmatrix} {\cos\;\theta} & {\sin\;\theta} \\ {{- \sin}\;\theta} & {\cos\;\theta} \end{pmatrix}},{{{where}\mspace{14mu}\theta} \in {\left\lbrack {0,\frac{\pi}{2}} \right\rbrack.}}} & (6) \end{matrix}$

In various embodiments of the present invention, only two angles i.e., θ and φ₁₁-φ₂₁ are fed back to the transmitter. (530, FIG. 5) The first angle, θ, unambiguously represents {tilde over (V)}, and the second angle, φ₁₁-φ₂₁, unambiguously represents P_(L). (520, FIG. 5) In other embodiments of the present invention, a trigonometric function of θ may be selected as a parameter to feed back. For example, cos θ may be fed back as a parameter to represent {tilde over (V)}. In still further embodiments, another parameter may be selected that may unambiguously describe {tilde over (V)}.

The phase information in P_(R) may be discarded. Equation (1) can be rewritten as

$\begin{matrix} \begin{matrix} {H = {UDV}^{\prime}} \\ {= {{UD}\left( {P_{L}\overset{\sim}{V}P_{R}} \right)}^{\prime}} \\ {= {U{\underset{\overset{\sim}{D}}{\underset{︸}{{DP}_{R}^{\prime}}}\left( \underset{\overset{–}{V}}{\underset{︸}{P_{L}\overset{\sim}{V}}} \right)}^{\prime}}} \\ {= {\underset{\overset{\sim}{U}}{\underset{︸}{{UP}_{R}^{\prime}}}{D\left( \underset{\overset{–}{V}}{\underset{︸}{P_{L}\overset{\sim}{V}}} \right)}^{\prime}}} \end{matrix} & (7) \end{matrix}$

where we have used the fact that D and P′_(R) are diagonal and therefore commute. It should be noted that H=ŨD V′ is also a singular value decomposition of H. For the SVD algorithm, the change from U to Ũ only changes the multiplication matrix on the receiver side. When H is a m×n matrix with m≠n, we can still write H=U{tilde over (D)} V′ and the effect of beam forming with V amounts to a rotation in the I/Q plane, which may be taken care of by the training process. Therefore, feeding back V to the transmitter is sufficient for the SVD algorithm. Since V is fully determined by θ and φ₁₁-φ₂₁, only two angles are required to feedback and they are between

$\left\lbrack {0,\frac{\pi}{2}} \right\rbrack$ and (−π, π].

As stated above, the unitary matrix V may be factored into the product of three matrices:

$\begin{matrix} \begin{matrix} {V = {\begin{pmatrix} 1 & 0 \\ 0 & {\mathbb{e}}^{i{({\phi_{21} - \phi_{11}})}} \end{pmatrix}\begin{pmatrix} b_{11} & b_{12} \\ {- b_{12}} & b_{11} \end{pmatrix}\begin{pmatrix} {\mathbb{e}}^{{\mathbb{i}}\;\phi_{11}} & 0 \\ 0 & {\mathbb{e}}^{{\mathbb{i}}\;\phi_{12}} \end{pmatrix}}} \\ {= {\begin{pmatrix} 1 & 0 \\ 0 & {\mathbb{e}}^{{\mathbb{i}}{({\phi_{21} - \phi_{11}})}} \end{pmatrix}\begin{pmatrix} {\cos\;\theta} & {\sin\;\theta} \\ {{- \sin}\;\theta} & {\cos\;\theta} \end{pmatrix}\begin{pmatrix} {\mathbb{e}}^{{\mathbb{i}}\;\phi_{11}} & 0 \\ 0 & {\mathbb{e}}^{{\mathbb{i}}\;\phi_{12}} \end{pmatrix}}} \end{matrix} & (8) \end{matrix}$

where θ and φ₂₁-φ₁₁ are between

$\left\lbrack {0,\frac{\pi}{2}} \right\rbrack$ and (−π, π]. The parameters θ and φ₂₁-φ₁₁ may be obtained at the receiver as follows: θ=arccos(abs(v ₁₁)),θε[0,π/2]  (9)

$\begin{matrix} {\phi_{ij} = \left\{ \begin{matrix} {{{\arctan\left( \frac{{Im}\left( v_{ij} \right)}{{Re}\left( v_{ij} \right)} \right)} + {\pi\text{/}2}},} & {{{Im}\left( v_{ij} \right)} \geq 0} \\ {{{\arctan\left( \frac{{Im}\left( v_{ij} \right)}{{Re}\left( v_{ij} \right)} \right)} + {3\pi\text{/}2}},} & {{{Im}\left( v_{ij} \right)} < 0} \end{matrix} \right.} & (10) \end{matrix}$

and the receiver may quantize θ and φ₂₁-φ₁₁ and feed them back to the transmitter as parameters that represent V. The transmitter may reconstruct V by determining the amplitudes using θ, and applying a phase rotation to the bottom row using φ₂₁-φ₁₁.

$\begin{matrix} {\overset{\_}{V} = \begin{pmatrix} {\cos\;\theta} & {\sin\;\theta} \\ {{- \sin}\;\theta\mspace{14mu}{\mathbb{e}}^{{\mathbb{i}}{({\phi_{21} - \phi_{11}})}}} & {\cos\;\theta\mspace{14mu}{\mathbb{e}}^{{\mathbb{i}}{({\phi_{21} - \phi_{11}})}}} \end{pmatrix}} & (11) \end{matrix}$

The transmitter may then use V for beamforming: x= Vd   (12) 3×3 Beamforming Matrices

Any complex, unit 3-vector may be written as

$\begin{matrix} {v = {\begin{bmatrix} v_{1} \\ v_{2} \\ v_{3} \end{bmatrix} = {{\mathbb{e}}^{{\mathbb{i}}\;\theta_{1}}\begin{bmatrix} {\cos\left( \phi_{1} \right)} \\ {{\sin\left( \phi_{1} \right)}{\cos\left( \phi_{2} \right)}{\mathbb{e}}^{{\mathbb{i}}\;\theta_{2}}} \\ {{\sin\left( \phi_{1} \right)}{\sin\left( \phi_{2} \right)}{\mathbb{e}}^{{\mathbb{i}}\;\theta_{3}}} \end{bmatrix}}}} & (13) \end{matrix}$ where ∥v∥ ² =∥v ₁∥² +∥v ₂∥² +∥v ₃∥²=1; φ₁,φ₂ ε└0,π/2┘ and θ₁,θ₂,θ₃ε[−π,π).

Further, any unitary 3 by 3 matrix may be written as

$\begin{matrix} {V = {\left\lbrack {v_{1}\mspace{14mu} v_{2}\mspace{14mu} v_{3}} \right\rbrack = \begin{bmatrix} {{\mathbb{e}}^{i\;\theta_{11}}{\cos\left( \phi_{11} \right)}} & {{\mathbb{e}}^{{\mathbb{i}\theta}_{12}}{\cos\left( \phi_{12} \right)}} & {{\mathbb{e}}^{{\mathbb{i}\theta}_{13}}{\cos\left( \phi_{13} \right)}} \\ {{\mathbb{e}}^{{\mathbb{i}}\;\theta_{11}}{\mathbb{e}}^{{\mathbb{i}\theta}_{21}}{\sin\left( \phi_{11} \right)}{\cos\left( \phi_{21} \right)}} & {{\mathbb{e}}^{{\mathbb{i}\theta}_{12}}{\mathbb{e}}^{{\mathbb{i}\theta}_{22}}{\sin\left( \phi_{12} \right)}{\cos\left( \phi_{22} \right)}} & {{\mathbb{e}}^{{\mathbb{i}\theta}_{13}}{\mathbb{e}}^{{\mathbb{i}\theta}_{23}}{\sin\left( \phi_{13} \right)}{\cos\left( \phi_{23} \right)}} \\ {{\mathbb{e}}^{{\mathbb{i}}\;\theta_{11}}{\mathbb{e}}^{{\mathbb{i}\theta}_{31}}{\sin\left( \phi_{11} \right)}{\sin\left( \phi_{21} \right)}} & {{\mathbb{e}}^{{\mathbb{i}\theta}_{12}}{\mathbb{e}}^{{\mathbb{i}\theta}_{32}}{\sin\left( \phi_{12} \right)}{\sin\left( \phi_{22} \right)}} & {{\mathbb{e}}^{{\mathbb{i}\theta}_{13}}{\mathbb{e}}^{{\mathbb{i}\theta}_{33}}{\sin\left( \phi_{13} \right)}{\sin\left( \phi_{23} \right)}} \end{bmatrix}}} & (14) \end{matrix}$

where v′_(j)v_(j)=1 and v′_(j)v_(k)=0 for j,k=1,2,3. The phases on the first row and the first column can be factored as the product of the following three matrices:

$\begin{matrix} {\mspace{79mu}{{V = {\underset{\underset{P_{L}}{︸}}{\begin{bmatrix} 1 & 0 & 0 \\ 0 & {\mathbb{e}}^{\;{\mathbb{i}\theta}_{21}} & 0 \\ 0 & 0 & {\mathbb{e}}^{{\mathbb{i}\theta}_{31}} \end{bmatrix}}\mspace{79mu}\underset{\overset{\sim}{V}}{\underset{︸}{\begin{bmatrix} {\cos\left( \phi_{11} \right)} & {\cos\left( \phi_{12} \right)} & {\cos\left( \phi_{13} \right)} \\ {{\sin\left( \phi_{11} \right)}{\cos\left( \phi_{21} \right)}} & {{\mathbb{e}}^{{\mathbb{i}\varphi}_{22}}{\sin\left( \phi_{12} \right)}{\cos\left( \phi_{22} \right)}} & {{\mathbb{e}}^{{\mathbb{i}\varphi}_{23}}{\sin\left( \phi_{13} \right)}{\cos\left( \phi_{23} \right)}} \\ {{\sin\left( \phi_{11} \right)}{\sin\left( \phi_{21} \right)}} & {{\mathbb{e}}^{{\mathbb{i}\varphi}_{32}}{\sin\left( \phi_{12} \right)}{\sin\left( \phi_{22} \right)}} & {{\mathbb{e}}^{{\mathbb{i}\varphi}_{33}}{\sin\left( \phi_{13} \right)}{\sin\left( \phi_{23} \right)}} \end{bmatrix}}}}}\mspace{79mu}\begin{matrix} \underset{︸}{\begin{bmatrix} {\mathbb{e}}^{{\mathbb{i}\theta}_{11}} & 0 & 0 \\ 0 & {\mathbb{e}}^{{\mathbb{i}\theta}_{12}} & 0 \\ 0 & 0 & {\mathbb{e}}^{{\mathbb{i}\theta}_{13}} \end{bmatrix}} \\ P_{R} \end{matrix}}} & (15) \end{matrix}$ where P_(L) and P_(R) are pure phase matrices and diagonal. P_(R) is generated by factoring phase values from each column of V, (610, FIG. 6) and P_(L) is found by factoring phase values from each row of V, and where φ_(jk)ε└0,π/2┘ and cos (φ_(jk)), cos (φ_(jk)), sin (φ_(jk))≧0. {tilde over (V)} is a magnitude matrix that includes all of the magnitude information originally present in the entries of V. As used herein, the term “magnitude matrix” refers to a matrix that remains after P_(L) and P_(R) are factored out of the original beamforming matrix. As shown in the above example, one or more entries in a magnitude matrix may include phase information. It should be noted that {tilde over (V)}=[{tilde over (v)}₁{tilde over (v)}₂{tilde over (v)}₃] is still unitary since the phase factorization doesn't change the unitary property.

In various embodiments of the present invention, two parameters are chosen to represent P_(L), four parameters are chosen to represent {tilde over (V)}, and P_(R) is discarded. In some embodiments, the angles θ₂₁, θ₃₁ are selected as parameters to represent P_(L). Matrix {tilde over (V)} can be determined by four parameters and a sign bit, and there are many combinations of the four parameters that are subsets of all the angles in {tilde over (V)}. Different combinations result in different complexities in the reconstruction of {tilde over (V)} at the transmitter. It should be noted that the complexity of extracting all the angles of {tilde over (V)} is relatively low compared to that of the construction of {tilde over (V)} based on four parameters. Instead of directly sending angles back, some embodiments may send functions of the selected four angles back. For example, common trigonometric functions such as sin( ), cos( ), and tan( ) may be selected. The various embodiments of the present invention contemplate all possible sets of four parameters to represent {tilde over (V)}. One set of four parameters φ₁₁,φ₁₂,φ₂₁,φ₂₂ and the sign of φ₂₂ provide a solution that is now elaborated. The extraction of the angles φ₁₁,φ₁₂,φ₂₁,φ₂₂ may be performed as: φ₁₁=arccos(|v₁₁|)  (16) φ₁₂=arccos(|v₁₂|)  (17)

$\begin{matrix} {\phi_{12} = {\arctan\left( \frac{v_{31}}{v_{21}} \right)}} & (18) \\ {\phi_{22} = {\arctan\left( \frac{v_{32}}{v_{22}} \right)}} & (19) \end{matrix}$

It should be noted that φ₁₁,φ₁₂,φ₂₁,φ₂₂ are all within [0,π/2] instead of [0,π] and the sign of φ₂₂ takes only one bit. In various embodiments, the feedback includes one angle in [0,π] and three angles in [0,π/2].

In embodiments using the above parameters to represent P_(L) and {tilde over (V)}, the receiver quantizes θ₂₁,θ₃₁, φ₁₁,φ₁₂,φ₂₁,φ₂₂ and feeds them back to the transmitter along with sign(φ₂₂), which can be found as sign(φ₂₂)=sign(angle({tilde over (v)}₂₂)). (620, 630, FIG. 6)

The receiver may receive the parameters, reconstruct {tilde over (V)}, and perform beamforming. The outline of the reconstruction of {tilde over (V)} is now shown as: computation of φ₂₂, φ₃₂ to reconstruct {tilde over (v)}₂, the second column of {tilde over (V)}; and computation of {tilde over (v)}₃, the third column of {tilde over (V)} using the unitary property of {tilde over (V)}. We rewrite {tilde over (V)} as

$\begin{matrix} {\overset{\sim}{V} = \begin{bmatrix} {\cos\left( \phi_{11} \right)} & {\cos\left( \phi_{12} \right)} & {\overset{\sim}{v}}_{13} \\ {{\sin\left( \phi_{11} \right)}{\cos\left( \phi_{21} \right)}} & {{\mathbb{e}}^{{\mathbb{i}\varphi}_{22}}{\sin\left( \phi_{12} \right)}{\cos\left( \phi_{22} \right)}} & {\overset{\sim}{v}}_{23} \\ {{\sin\left( \phi_{11} \right)}{\sin\left( \phi_{21} \right)}} & {{\mathbb{e}}^{{\mathbb{i}\varphi}_{32}}{\sin\left( \phi_{12} \right)}{\sin\left( \phi_{22} \right)}} & {\overset{\sim}{v}}_{33} \end{bmatrix}} & (20) \end{matrix}$

Since {tilde over (v)}₂ is orthogonal to {tilde over (v)}₁, we have v′₁v₂=0 or c ₁ +c ₂ e ^(iφ22) +c ₂ e ^(iφ32)=0  (21)

where c ₁=cos(φ₁₁)cos(φ₁₂) c ₂=sin(φ₁₁)cos(φ₂₁)sin(φ₁₂)cos(φ₂₂)  (22) c ₃=sin(φ₁₁)sin(φ₂₁)sin(φ₁₂)sin(φ₂₂)

The c_(j) are all greater than or equal to zero since φ₁₁,φ₁₂,φ₂₁,φ₂₂ are all within [0,π/2]. Equation (21) can be explicitly solved by using laws of cosine. The solutions of φ₂₂,φ₃₂ are

$\begin{matrix} \begin{matrix} {\varphi_{22} = {{{sign}\left( \varphi_{22} \right)}\left\lbrack {\arccos\left( \frac{c_{1}^{2} + c_{2}^{2} - c_{3}^{2}}{2c_{1}c_{2}} \right)} \right\rbrack}} \\ {\varphi_{32} = {- {{{sign}\left( \varphi_{22} \right)}\left\lbrack {\arccos\left( \frac{c_{1}^{2} + c_{3}^{2} - c_{2}^{2}}{2c_{1}c_{3}} \right)} \right\rbrack}}} \end{matrix} & (23) \end{matrix}$

Since {tilde over (V)}′ is also unitary, the norm of the first row is 1. Considering {tilde over (v)}₁₃=cos(φ₁₃) is a positive number, we solve {tilde over (v)}₁₃ as {tilde over (v)} ₁₃=√{square root over (1−cos²(φ₁₁)−cos²(φ₁₂))}{square root over (1−cos²(φ₁₁)−cos²(φ₁₂))}  (24)

Since {tilde over (V)}′ is unitary, the second row of {tilde over (V)} is orthogonal to the second row. {tilde over (v)}₂₃ can be solved as

$\begin{matrix} {{\overset{\sim}{v}}_{23} = \frac{{{- {\cos\left( \phi_{11} \right)}}{\sin\left( \phi_{11} \right)}{\cos\left( \phi_{21} \right)}} - {{\cos\left( \phi_{12} \right)}{\sin\left( \phi_{12} \right)}{\cos\left( \phi_{22} \right)}{\mathbb{e}}^{{\mathbb{i}\varphi}_{22}}}}{\sqrt{1 - {\cos^{2}\left( \phi_{11} \right)} - {\cos^{2}\left( \phi_{12} \right)}}}} & (25) \end{matrix}$

Similarly, {tilde over (v)}₃₃ is

$\begin{matrix} {{\overset{\sim}{v}}_{33} = \frac{{{- {\cos\left( \phi_{11} \right)}}{\sin\left( \phi_{11} \right)}{\sin\left( \phi_{21} \right)}} - {{\cos\left( \phi_{12} \right)}{\sin\left( \phi_{12} \right)}{\sin\left( \phi_{22} \right)}{\mathbb{e}}^{{\mathbb{i}\varphi}_{32}}}}{\sqrt{1 - {\cos^{2}\left( \phi_{11} \right)} - {\cos^{2}\left( \phi_{12} \right)}}}} & (26) \end{matrix}$

Remembering that

$\begin{matrix} {{P_{L} = \begin{bmatrix} 1 & 0 & 0 \\ 0 & {\mathbb{e}}^{{\mathbb{i}\theta}_{21}} & 0 \\ 0 & 0 & {\mathbb{e}}^{{\mathbb{i}\theta}_{31}} \end{bmatrix}},} & (27) \end{matrix}$

beamforming may be performed as: x=P_(L){tilde over (V)}d  (28)

FIG. 2 shows a flowchart in accordance with various embodiments of the present invention. In some embodiments, method 200 may be used in, or for, a wireless system that utilizes MIMO technology. In some embodiments, method 200, or portions thereof, is performed by a wireless communications device, embodiments of which are shown in the various figures. In other embodiments, method 200 is performed by a processor or electronic system. Method 200 is not limited by the particular type of apparatus or software element performing the method. The various actions in method 200 may be performed in the order presented, or may be performed in a different order. Further, in some embodiments, some actions listed in FIG. 2 are omitted from method 200.

Method 200 is shown beginning at block 210 in which channel state information is estimated from received signals. The channel state information may include the channel state matrix H described above. At 220, a beamforming matrix is determined from the channel state information. In some embodiments, this corresponds to performing singular value decomposition (SVD) as described above with reference to equations (1) and (7). The beamforming matrix V is also described above.

At 230, a phase angle is factored out of each column of the beamforming matrix. For example, as shown above in equations (5), (8), and (15), the phase matrix P_(R) may be factored out of the beamforming matrix and discarded. At 240, additional phase information is factored from the beamforming matrix to yield a phase matrix and an magnitude matrix. In the various embodiments of the present invention described above, the additional phase information is represented by the phase matrix P_(L), and the magnitude matrix is represented by {tilde over (V)}. The magnitude matrix includes the magnitude information from the original beamforming matrix V, and may or may not include phase information. Accordingly, the entries in {tilde over (V)} may be scalars or complex numbers.

At 250, the phase matrix and magnitude matrix are represented using N²−N parameters, where N is a number of spatial channels. For example, in the 2×2 embodiments described above, N=2, and the phase matrix and magnitude matrix are represented by two parameters. One parameter, θ, is used to represent the magnitude matrix and one parameter, φ₁₁-φ₂₁, is used to represent the phase matrix. Also for example, in the 3×3 embodiments described above, N=3, and the phase matrix and magnitude matrix are represented by six parameters and a sign bit. The phase matrix is represented by two parameters, and the magnitude matrix is represented by four parameters and a sign bit. The choice of parameters to represent the magnitude matrix is large.

At 260, the parameters are quantized. They can be quantized individually or jointly. The parameters are quantized in the ranges appropriate for the range of the parameters selected. For example, in the 2×2 embodiments described above, θ and φ₁₁-φ₂₁, are quantized between

$\left\lbrack {0,\frac{\pi}{2}} \right\rbrack$ and (−π,π], respectively. At 270, the quantized parameters are transmitted. The quantized parameters may be transmitted using any type of protocol or any type of communications link, including a wireless link such as a wireless link between stations like those described with reference to FIG. 1.

FIG. 3 shows a flowchart in accordance with various embodiments of the present invention. In some embodiments, method 300 may be used in, or for, a wireless system that utilizes MIMO technology. In some embodiments, method 300, or portions thereof, is performed by a wireless communications device, embodiments of which are shown in the various figures. In other embodiments, method 300 is performed by a processor or electronic system. Method 300 is not limited by the particular type of apparatus or software element performing the method. The various actions in method 300 may be performed in the order presented, or may be performed in a different order. Further, in some embodiments, some actions listed in FIG. 3 are omitted from method 300.

Method 300 is shown beginning at block 310 in which at least one angle parameter is received. This may correspond to a transmitter receiving one or more angle parameters that represent a magnitude matrix. For example, the at least one angle parameter may include θ as described above with reference to equation (6), or may include φ₁₁,φ₁₂,φ₂₁,φ₂₂, as described above with reference to equations (15)-(19).

At 320, magnitudes of entries in a beamforming matrix are determined from the at least one angle parameter. For example, as shown in equation (11), the magnitude of the entries in a 2×2 beamforming matrix may be determined from the angle parameter θ, and as shown in equations (20) and (24)-(26), the magnitude of the entries in a 3×3 beamforming matrix may be determined from the angle parameters φ₁₁,φ₁₂,φ₂₁, and φ₂₂.

At 330, at least one phase parameter is received. This may correspond to the transmitter receiving one or more phase parameters that represent a phase matrix. For example, the at least one phase parameter may include φ₂₁-φ₁₁ as described above with reference to equations (5) and (8), or may include φ₁₁,φ₁₂,φ₂₁,φ₂₂, as described above with reference to equations (15)-(19). At 340, the at least one phase parameter may be applied to at least one row in the beamforming matrix. For example, the phase matrix and magnitude matrix may be multiplied as shown in equation (11) or equation (28). Further, the beamforming matrix may be used in beamforming as shown in equation (28).

FIG. 4 shows a system diagram in accordance with various embodiments of the present invention. Electronic system 400 includes antennas 410, physical layer (PHY) 430, media access control (MAC) layer 440, Ethernet interface 450, processor 460, and memory 470. In some embodiments, electronic system 400 may be a station capable of factoring beamforming matrices and quantizing parameters as described above with reference to the previous figures. In other embodiments, electronic system may be a station that receives quantized parameters, and performs beamforming in a MIMO system. For example, electronic system 400 may be utilized in a wireless network as station 102 or station 104 (FIG. 1). Also for example, electronic system 400 may be a station capable of performing the calculations shown in any of the equations (1)-(28), above.

In some embodiments, electronic system 400 may represent a system that includes an access point or mobile station as well as other circuits. For example, in some embodiments, electronic system 400 may be a computer, such as a personal computer, a workstation, or the like, that includes an access point or mobile station as a peripheral or as an integrated unit. Further, electronic system 400 may include a series of access points that are coupled together in a network.

In operation, system 400 sends and receives signals using antennas 410, and the signals are processed by the various elements shown in FIG. 4. Antennas 410 may be an antenna array or any type of antenna structure that supports MIMO processing. System 400 may operate in partial compliance with, or in complete compliance with, a wireless network standard such as an 802.11 standard.

Physical layer (PHY) 430 is coupled to antennas 410 to interact with a wireless network. PHY 430 may include circuitry to support the transmission and reception of radio frequency (RF) signals. For example, in some embodiments, PHY 430 includes an RF receiver to receive signals and perform “front end” processing such as low noise amplification (LNA), filtering, frequency conversion or the like. Further, in some embodiments, PHY 430 includes transform mechanisms and beamforming circuitry to support MIMO signal processing. Also for example, in some embodiments, PHY 430 includes circuits to support frequency up-conversion, and an RF transmitter.

Media access control (MAC) layer 440 may be any suitable media access control layer implementation. For example, MAC 440 may be implemented in software, or hardware or any combination thereof. In some embodiments, a portion of MAC 440 may be implemented in hardware, and a portion may be implemented in software that is executed by processor 460. Further, MAC 440 may include a processor separate from processor 460.

In operation, processor 460 reads instructions and data from memory 470 and performs actions in response thereto. For example, processor 460 may access instructions from memory 470 and perform method embodiments of the present invention, such as method 200 (FIG. 2) or method 300 (FIG. 3) or methods described with reference to other figures. Processor 460 represents any type of processor, including but not limited to, a microprocessor, a digital signal processor, a microcontroller, or the like.

Memory 470 represents an article that includes a machine readable medium. For example, memory 470 represents a random access memory (RAM), dynamic random access memory (DRAM), static random access memory (SRAM), read only memory (ROM), flash memory, or any other type of article that includes a medium readable by processor 460. Memory 470 may store instructions for performing the execution of the various method embodiments of the present invention. Memory 470 may also store beamforming matrices or beamforming vectors.

Although the various elements of system 400 are shown separate in FIG. 4, embodiments exist that combine the circuitry of processor 460, memory 470, Ethernet interface 450, and MAC 440 in a single integrated circuit. For example, memory 470 may be an internal memory within processor 460 or may be a microprogram control store within processor 460. In some embodiments, the various elements of system 400 may be separately packaged and mounted on a common circuit board. In other embodiments, the various elements are separate integrated circuit dice packaged together, such as in a multi-chip module, and in still further embodiments, various elements are on the same integrated circuit die.

Ethernet interface 450 may provide communications between electronic system 400 and other systems. For example, in some embodiments, electronic system 400 may be an access point that utilizes Ethernet interface 450 to communicate with a wired network or to communicate with other access points. Some embodiments of the present invention do not include Ethernet interface 450. For example, in some embodiments, electronic system 400 may be a network interface card (NIC) that communicates with a computer or network using a bus or other type of port.

Although the present invention has been described in conjunction with certain embodiments, it is to be understood that modifications and variations may be resorted to without departing from the spirit and scope of the invention as those skilled in the art readily understand. Such modifications and variations are considered to be within the scope of the invention and the appended claims. 

1. A method performed by a wireless station in a closed loop multiple-input-multiple-output (MIMO) wireless network, the method comprising: estimating channel state information from received signals; determining a beamforming matrix from the channel state information; factoring phase information out of the beamforming matrix; factoring additional phase information from each row of the beamforming matrix to yield a phase matrix and a magnitude matrix; representing the phase matrix and the magnitude matrix using N²−N parameters where N is a number of spatial channels; quantizing the parameters; and transmitting from the wireless station the parameters describing the beamforming matrix without the phase information.
 2. The method of claim 1 wherein factoring phase information out of a beamforming matrix comprises factoring a phase angle out of each column in the beamforming matrix.
 3. The method of claim 1 wherein transmitting comprises transmitting at least one parameter to represent the phase matrix and transmitting at least one parameter to represent the magnitude matrix.
 4. The method of claim 3 wherein: the beamforming matrix includes two rows and two columns; the at least one parameter to represent the phase matrix consists of a first parameter; and the at least one parameter to represent the magnitude matrix consists of a second parameter.
 5. The method of claim 4 wherein the first parameter consists of an angle.
 6. The method of claim 4 wherein the first parameter consists of a function of an angle.
 7. A method performed by a wireless station in a closed loop multiple-input-multiple-output (MIMO) wireless network, the method comprising: factoring a 2×2 beamforming matrix into a plurality of matrices, a first of the plurality of matrices having entries that include magnitude information from the beamforming matrix, wherein the plurality of matrices further includes two matrices with phase information, and wherein one of the two matrices is represented by a second parameter, and the other of the two matrices is discarded; representing the first of the plurality of matrices with a first parameter; and transmitting the first parameter from the wireless station.
 8. The method of claim 7 wherein the first parameter comprises an angle.
 9. The method of claim 7 wherein the first parameter comprises a trigonometric function of an angle.
 10. A method performed by a wireless station in a closed loop multiple-input-multiple-output (MIMO) wireless network, the method comprising: factoring a phase angle from each column of a 3×3 beamforming matrix; representing the beamforming matrix using six parameters; and transmitting the six parameters from the wireless station.
 11. The method of claim 10 further comprising transmitting the six parameters on a wireless link.
 12. The method of claim 10 further comprising factoring phase information from each row of the 3×3 beamforming matrix.
 13. The method of claim 12 wherein two of the six parameters are selected to represent the phase information factored from each row.
 14. A method performed by a wireless station in a closed loop multiple-input-multiple-output (MIMO) wireless network, the method comprising: receiving, at the wireless station, at least one angle parameter over a wireless link; determining magnitudes of entries in a beamforming matrix from the at least one angle parameter; receiving, at the wireless station, at least one phase parameter; and applying the at least one phase parameter to at least one row in the beamforming matrix.
 15. The method of claim 14 wherein: the beamforming matrix comprises two rows and two columns; the at least one angle parameter consists of one angle parameter; and the at least one phase parameter consists of one phase parameter.
 16. The method of claim 14 wherein: the beamforming matrix comprises three rows and three columns; the at least one angle parameter consists of four angle parameters; and the at least one phase parameter consists of two phase parameters. 